/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 24 Suppose \(W\) is a subspace of a... [FREE SOLUTION] | 91Ó°ÊÓ

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Suppose \(W\) is a subspace of a vector space \(V\). Show that the operations in Theorem \(10.15\) are well defined; namely, show that if \(u+W=u^{\prime}+W\) and \(v+W=v^{\prime}+W\), then (a) \((u+v)+W=\left(u^{\prime}+v^{\prime}\right)+W \quad\) and (b) \(k u+W=k u^{\prime}+W \quad\) for any \(k \in K\) (a) Because \(u+W=u^{\prime}+W\) and \(v+W=v^{\prime}+W\), both \(u-u^{\prime}\) and \(v-v^{\prime}\) belong to \(W\). But then \((u+v)-\left(u^{\prime}+v^{\prime}\right)=\left(u-u^{\prime}\right)+\left(v-v^{\prime}\right) \in W .\) Hence, \((u+v)+W=\left(u^{\prime}+v^{\prime}\right)+W .\) (b) Also, because \(u-u^{\prime} \in W\) implies \(k\left(u-u^{\prime}\right) \in W\), then \(k u-k u^{\prime}=k\left(u-u^{\prime}\right) \in W\); accordingly, \(k u+W=k u^{\prime}+W\)

Short Answer

Expert verified
In summary, given that $u+W = u'+W$ and $v+W = v'+W$, we proved that $(u+v)+W = (u'+v')+W$ and $ku+W = ku'+W$ for any scalar $k$. This demonstrates that the operations in Theorem 10.15 are well defined.

Step by step solution

01

The Given Information

We are given two equations: 1. u+W = u'+W, and 2. v+W = v'+W It is given that both u-u' and v-v' belong to W because W is a subspace.
02

Proving (u+v)+W = (u'+v')+W

We want to show that (u+v)+W = (u'+v')+W. From the given information, we have: (u+v) - (u'+v') = (u-u') + (v-v') Since u-u' and v-v' belong to W, their sum also belongs to W: (u+v) - (u'+v') ∈ W So, it follows that (u+v) + W = (u'+v') + W.
03

Proving ku+W = ku'+W for any scalar k

We want to show that ku+W = ku'+W for any scalar k. From the given information, we have u-u' ∈ W. By multiplying both sides by the scalar k, we get: k(u-u') ∈ W Which is equivalent to: ku - ku' ∈ W So, it follows that ku+W = ku'+W for any scalar k. In conclusion, we have proved that: 1. (u+v)+W = (u'+v')+W 2. ku+W = ku'+W for any scalar k. This shows that the operations in Theorem 10.15 are well defined for the given conditions.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Subspace
A subspace is a crucial concept in the study of vector spaces. It simply refers to a subset of a vector space that is itself a vector space under the same addition and scalar multiplication operations. To qualify as a subspace, three main conditions must be satisfied:
  • The zero vector of the main vector space must be included in the subspace.
  • It must be closed under addition, meaning if you add two vectors from the subspace, the resulting vector is also in the subspace.
  • It must be closed under scalar multiplication, implying if you multiply a vector from the subspace by a scalar, the result stays within the subspace.
These conditions ensure that the subspace behaves consistently within its parent vector space, simplifying the study of vector operations and properties.
Addition of Vectors
In the realm of vector spaces, the addition of vectors is a fundamental operation that follows specific rules. When two vectors are added, their corresponding components are summed together. Mathematically, if you have vectors \(u = [u_1, u_2, ..., u_n]\) and \(v = [v_1, v_2, ..., v_n]\), their sum \(u+v\) produces a new vector \([u_1+v_1, u_2+v_2, ..., u_n+v_n]\).
This operation's importance is highlighted when proving properties of subspaces. As derived in the exercise, if \(u+W = u'+W\) and \(v+W = v'+W\), then \((u+v)+W = (u'+v')+W\). This implies vector addition in the context of subspaces results in a consistent, predictable outcome, maintaining the structure of the vector space.
Scalar Multiplication
Scalar multiplication involves expanding a vector by a scalar \(k\), which is a number from the underlying field. In mathematical terms, given a vector \(u = [u_1, u_2, ..., u_n]\) and a scalar \(k\), the product \(ku\) translates to \( [ku_1, ku_2, ..., ku_n]\).
In relation to subspaces, scalar multiplication helps verify if vector operations remain within the subspace. In the exercise, where \(u-u'\) belongs to \(W\), applying scalar multiplication retains this membership: \(ku-ku' = k(u-u') \in W\). This confirms that for any scalar \(k\), \(ku+W = ku'+W\), thereby ensuring that the properties of scalar multiplication hold true even within subspaces.
Well-Defined Operations
In vector spaces and their subspaces, well-defined operations are crucial for establishing consistency and predictability. An operation is well-defined if it yields the same result regardless of how it's computed or represented.
Within the given exercise, we proved that addition and scalar multiplication operations with respect to cosets, such as \((u+v)+W\) and \(ku+W\), are well-defined. This means despite the representations \(u+W=u'+W\) or \(v+W=v'+W\), the operations consistently produce the same outcome.
To sum up, well-defined operations ensure that mathematical manipulations involving vectors and subspaces lead to clear and unambiguous results, maintaining the structural integrity of vector spaces and their subspaces.

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Most popular questions from this chapter

Let \(E_{1}, \ldots, E_{r}\) be linear operators on \(V\) such that (i) \(E_{i}^{2}=E_{i}\) (i.e., the \(E_{i}\) are projections); (ii) \(E_{i} E_{j}=0, i \neq j\); (iii) \(I=E_{1}+\cdots+E_{r}\) Prove that \(V=\operatorname{Im} E_{1} \oplus \cdots \oplus \operatorname{Im} E_{r}\)

Prove Theorem 10.1: Let \(T: V \rightarrow V\) be a linear operator whose characteristic polynomial factors into linear polynomials. Then \(V\) has a basis in which \(T\) is represented by a triangular matrix. The proof is by induction on the dimension of \(V\). If \(\operatorname{dim} V=1\), then every matrix representation of \(T\) is a \(1 \times 1\) matrix, which is triangular. Now suppose \(\operatorname{dim} V=n>1\) and that the theorem holds for spaces of dimension less than \(n .\) Because the characteristic polynomial of \(T\) factors into linear polynomials, \(T\) has at least one eigenvalue and so at least one nonzero eigenvector \(v\), say \(T(v)=a_{11} v .\) Let \(W\) be the one- dimensional subspace spanned by \(v\). Set \(\bar{V}=V / W .\) Then (Problem 10.26) \(\operatorname{dim} \bar{V}=\operatorname{dim} V-\operatorname{dim} W=n-1 .\) Note also that \(W\) is invariant under \(T .\) By Theorem \(10.16, T\) induces a linear operator \(\bar{T}\) on \(\bar{V}\) whose minimal polynomial divides the minimal polynomial of \(T\). Because the characteristic polynomial of \(T\) is a product of linear polynomials, so is its minimal polynomial, and hence, so are the minimal and characteristic polynomials of \(\bar{T}\). Thus, \(\bar{V}\) and \(\bar{T}\) satisfy the hypothesis of the theorem. Hence, by induction, there exists a basis \(\left\\{\bar{v}_{2}, \ldots, \bar{v}_{n}\right\\}\) of \(\bar{V}\) such that $$ \begin{aligned} &\bar{T}\left(\bar{v}_{2}\right)=a_{22} \bar{v}_{2} \\ &\bar{T}\left(\bar{v}_{3}\right)=a_{32} \bar{v}_{2}+a_{33} \bar{v}_{3} \\ &\cdots \ldots \ldots \cdots \\ &\bar{T}\left(\bar{v}_{n}\right)=a_{n 2} \bar{v}_{n}+a_{n 3} \bar{v}_{3}+\cdots+a_{n n} \bar{v}_{n} \end{aligned} $$Now let \(v_{2}, \ldots, v_{n}\) be elements of \(V\) that belong to the cosets \(v_{2}, \ldots, v_{n}\), respectively. Then \(\left\\{v, v_{2}, \ldots, v_{n}\right\\}\) is a basis of \(V\) (Problem 10.26). Because \(\bar{T}\left(v_{2}\right)=a_{22} \bar{v}_{2}\), we have $$ \bar{T}\left(\bar{v}_{2}\right)-a_{22} \bar{v}_{22}=0, \quad \text { and so } \quad T\left(v_{2}\right)-a_{22} v_{2} \in W $$ But \(W\) is spanned by \(v\); hence, \(T\left(v_{2}\right)-a_{22} v_{2}\) is a multiple of \(v\), say, $$ T\left(v_{2}\right)-a_{22} v_{2}=a_{21} v, \quad \text { and so } \quad T\left(v_{2}\right)=a_{21} v+a_{22} v_{2} $$ Similarly, for \(i=3, \ldots, n\) $$ T\left(v_{i}\right)-a_{i 2} v_{2}-a_{i 3} v_{3}-\cdots-a_{i i} v_{i} \in W, \quad \text { and so } \quad T\left(v_{i}\right)=a_{i 1} v+a_{i 2} v_{2}+\cdots+a_{i i} v_{i} $$ Thus, $$ \begin{aligned} &T(v)=a_{11} v \\ &T\left(v_{2}\right)=a_{21} v+a_{22} v_{2} \\ &\ldots \ldots \ldots \cdots \cdots \cdots \cdots \cdots \cdots \cdots \\ &T\left(v_{n}\right)=a_{n 1} v+a_{n 2} v_{2}+\cdots+a_{n n} v_{n} \end{aligned} $$ and hence the matrix of \(T\) in this basis is triangular.

Suppose \(T: V \rightarrow V\) is linear and suppose \(T=T_{1} \oplus T_{2}\) with respect to a \(T\)-invariant direct-sum decomposition \(V=U \oplus W .\) Show that (a) \(m(t)\) is the least common multiple of \(m_{1}(t)\) and \(m_{2}(t)\), where \(m(t), m_{1}(t), m_{2}(t)\) are the minimum polynomials of \(T, T_{1}, T_{2}\), respectively. (b) \(\Delta(t)=\Delta_{1}(t) \Delta_{2}(t)\), where \(\Delta(t), \Delta_{1}(t), \Delta_{2}(t)\) are the characteristic polynomials of \(T, T_{1}, T_{2}\) respectively. (a) By Problem 10.6, each of \(m_{1}(t)\) and \(m_{2}(t)\) divides \(m(t)\). Now suppose \(f(t)\) is a multiple of both \(m_{1}(t)\) and \(m_{2}(t)\), then \(f\left(T_{1}\right)(U)=0\) and \(f\left(T_{2}\right)(W)=0 .\) Let \(v \in V\), then \(v=u+w\) with \(u \in U\) and \(w \in W\). Now $$ f(T) v=f(T) u+f(T) w=f\left(T_{1}\right) u+f\left(T_{2}\right) w=0+0=0 $$ That is, \(T\) is a zero of \(f(t)\). Hence, \(m(t)\) divides \(f(t)\), and so \(m(t)\) is the least common multiple of \(m_{1}(t)\) and \(m_{2}(t)\) (b) By Theorem \(10.5, T\) has a matrix representation \(M=\left[\begin{array}{ll}A & 0 \\ 0 & B\end{array}\right]\), where \(A\) and \(B\) are matrix representations of \(T_{1}\) and \(T_{2}\), respectively. Then, as required, $$ \Delta(t)=|t I-M|=\left|\begin{array}{cc} t I-A & 0 \\ 0 & t I-B \end{array}\right|=|t I-A||t I-B|=\Delta_{1}(t) \Delta_{2}(t) $$Prove Theorem 10.7: Suppose \(T: V \rightarrow V\) is linear, and suppose \(f(t)=g(t) h(t)\) are polynomials such that \(f(T)=\mathbf{0}\) and \(g(t)\) and \(h(t)\) are relatively prime. Then \(V\) is the direct sum of the \(T\)-invariant subspaces \(U\) and \(W\) where \(U=\operatorname{Ker} g(T)\) and \(W=\operatorname{Ker} h(T)\).

Let \(W\) be the solution space of the linear equation \\[ a_{1} x_{1}+a_{2} x_{2}+\dots+a_{n} x_{n}=0, \quad a_{i} \in K \\] and let \(v=\left(b_{1}, b_{2}, \ldots, b_{n}\right) \in K^{n} .\) Prove that the coset \(v+W\) of \(W\) in \(K^{\prime \prime}\) is the solution set of the linear equation \\[ a_{1} x_{1}+a_{2} x_{2}+\dots+a_{n} x_{n}=b, \quad \text { where } \quad b=a_{1} b_{1}+\dots+a_{n} b_{n} \\]

Let \(W\) be the solution space of the homogeneous equation \(2 x+3 y+4 z=0\). Describe the cosets of \(W\) in \(\mathbf{R}^{3}\).

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